Content Based Image Retrieval for Community Retrieval from Given Nationality using an Efficient Combination Algorithm
Shaik. Rahamtula1, T. Jaya2
1Shaik. Rahamtula*, Research scholar, Department of Electronics and Communication Engineering, VELS Institute of Science Technology and Advanced Studies, Pallavaram, Chennai, Tamil Nadu, India.
2Dr. T. Jaya, Assistant Professor, Department of Electronics and Communication Engineering, VELS Institute of Science Technology and Advanced Studies, Pallavaram, Chennai, Tamil Nadu, India.
Manuscript received on October 16, 2019. | Revised Manuscript received on 21 October, 2019. | Manuscript published on November 10, 2019. | PP: 3003-3007 | Volume-9 Issue-1, November 2019. | Retrieval Number: A9124119119/2019©BEIESP | DOI: 10.35940/ijitee.A9124.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There is tremendous requirement of such technique which can fulfill the entire requirement for retrieval of an image from available dataset which comes under computer vision. In this paper we discussed about the one of the application of CBIR using an efficient combination of two techniques. The application is retrieval of people images from database that comes under minority. In this paper we used an efficient combination of color image histogram technique and edge orientation histogram technique by dividing original image into small subblocks. The feature vector is formed by combination of two features obtained by above methodologies. The final features obtained by query image will be compared with the feature vector of database images using a new Canberra Distance classifier. Proposed method is designed for multiple self-prepared and some collected from internet databases. Our method includes the efficient integration of features such as color, texture, shape and orientation. The proposed method is compared with state of art techniques to prove the stable and highest accuracy of proposed work.
Keywords: Integration of Features, Color Histogram, Edge Orientation Histogram, Canberra Distance, Content Based Image Retrieval.
Scope of the Article: Algorithm Engineering